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717 articles for “data utility”
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Scientometric Insights and Meta-Analysis of Japanese Encephalitis Research in India
Abstract: Japanese Encephalitis (JE) represents India’s critical public health issue, contributing significantly to regional morbidity and mortality. This study details the findings from a scientometric analysis of JE research conducted in India. Our study analyzed scientific publications to uncover trends, key contributors, gaps, and the thematic evolution within JE research, providing insights critical for shaping future research and policy directions. A comprehensive scientometric analysis of research on JE published in India …
Published in Research and Reviews: A Journal of Neuroscience · Vol. 16, Issue 1, 2026 · pp. 43–53 Read article
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Supervision of College Management Using Database Management System
Abstract: The college management system is a software application created with C programming and file handling methods. It serves as a centralized platform for overseeing diverse aspects of college operations, encompassing student details, course information, faculty records, enrollment management, attendance monitoring, grade administration, reporting, and administrative functions. It is designed to efficiently manage student, course, and faculty information in a college setting. The system utilizes files for data storage and conducts …
Published in Journal of Advanced Database Management & Systems · Vol. 11, Issue 2, 2024 · pp. 1–7 Read article
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The Symbiosis Between Spherical Refractive Error Cylindrical Refractive Error
Abstract: This study aimed to acknowledge the link between spherical refractive error and cylindrical refractive error, which is crucial for diagnosing and managing visual abnormalities productively. This research employed a multi-center, cross-sectional, analytical, and retrospective approach to investigate refractive errors. The objective results were refined subjectively to the best visual acuity with conventional clinical representations of refraction using the sphere, cylinder, and axis. The gathered data underwent analysis utilizing statistical software …
Published in Research and Reviews : A Journal of Medical Science and Technology · Vol. 13, Issue 1, 2024 · pp. 67–76 Read article
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A Dual-Model Deep Learning Framework for Early Alzheimer’s Detection Using Clinical Data and Neuroimaging with Architectural Performance Analysis
Abstract: Alzheimer’s disease (AD) poses a significant global health challenge due to its increasing prevalence and the absence of definitive cures. Early diagnosis is crucial for effective intervention and management. This study presents a dual-model deep learning framework for the early detection and classification of AD using both structured clinical data and neuroimaging datasets. Model 1 utilizes a greedy layer-wise autoencoder approach applied to structured data, achieving optimal binary classification accuracy …
Published in Research and Reviews: A Journal of Neuroscience · Vol. 16, Issue 1, 2026 · pp. 1–12 Read article
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Develop the Design of Sustainable Polymer Materials: Applying Reinforcement Learning, IoT-Enabled Monitoring, and Data-Driven Manufacturing Approaches
Abstract: Sustainable polymer materials development is a must due to resource constraints, environmental concerns, and the demand for designed materials with high performance. When it comes to material optimization, energy utilization, process unpredictability, and lifecycle sustainability, traditional polymer production methods have their challenges. Reinforcement Learning (RL), Internet of Things (IoT) monitoring, and data-driven production are utilized in the design and manufacturing of sustainable polymer materials. It is recommended to use Internet …
Published in Journal of Polymer & Composites · Vol. 14, Issue 3, 2026 Read article
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An Analytical Study of Mental Health to College Students
Abstract: The research aimed to explore variations in the mental well-being of university students, utilizing a 2X3X3 factorial design. Data gathering relied on the utilization of the "Mental Health Inventory" developed by Dr. D.G. Bhatt and G.R. Gida in 2006, with a sample selection conducted through the stratified random method. A total of 540 samples of college’s students were taken college from Bhavnagar city among them 270 from college girls and …
Published in Research and Reviews: A Journal of Health Professions · Vol. 14, Issue 1, 2024 · pp. 7–10 Read article
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Leveraging Full Stack Data Science for Healthcare Transformation: An Exploration of the Microsoft Intelligent Data Platform
Abstract: The rapid progress of the Fourth Industrial Revolution has been largely driven by the evolution of artificial intelligence (AI), with notable contributions from technologies such as Generative Pre-trained Transformers (GPT). This revolution has seen the convergence of physical, digital, and biological technologies, leading to transformative impacts across various sectors. Data science, serving as a crucial enabler, has enabled the development of intelligent value chains. However, the application of data science …
Published in Journal of Advanced Database Management & Systems · Vol. 11, Issue 3, 2024 · pp. 1–8 Read article
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Hybridization Method for Injection Moulding Process, Optimization with Melting Temperature Parameters
Abstract: Due to the production of plastic products with complex shapes, the plastic injection moulding manufacturing method has recently received a lot of attention. In order to improve manufacturing performance, the cycle time for the injection moulding process has been reduced, the defect known as dimensional warpage that results from temperature differences inside the mould has been reduced, and the mechanical tensile strength of the material has been increased so that …
Published in Journal of Polymer & Composites · Vol. 13, Issue 3, 2025 · pp. 337–345 Read article
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Multi-Screen Interface Applications in Graphical User Interface for Ornamental Efficiency in Computer Programming
Abstract: Use of multi-screen interfaces for graphical user interfaces (GUIs) has transformed the way we do computer programming by improving the speed, efficiency and usability. Also, these interfaces help programmers multitask easily by decoupling the different functionalities, code debugging, and data visualization in real-time through multiple terminals which cuts down context switching, thus maintaining workflow organization. Multi-screen GUI applications enable developers to organize their workspace and work efficiently, with customized or …
Published in International Journal of Computer Science Languages · Vol. 3, Issue 1, 2025 · pp. 27–31 Read article
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Botnet Beacon: Unveiling Covert Networks with Advanced AI Detection Strategies
Abstract: Securing information technology systems is paramount in today's interconnected world, where the reliability and security of networks and applications are of utmost importance. In this context, the development of a Botnet Detection System (BDS) that harnesses the power of AI classification algorithms becomes a critical endeavor. The primary objective of this work is to construct a comprehensive framework for a BDS that can efficiently gather network data and subject it …
Published in Research & Reviews: A Journal of Embedded System & Applications · Vol. 12, Issue 2, 2024 · pp. 26–32 Read article
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Ethical Consideration in the Use of Artificial Intelligence in Medicine and Healthcare
Abstract: Artificial Intelligence (AI) in medicine and healthcare offers tremendous potential for improving patient care, increasing the precision of diagnoses, and increasing operational efficiency. To ensure responsible application, however, the swift uptake of AI technologies also brings up important ethical concerns that need to be addressed. This article explores various ethical challenges in healthcare AI, including concerns about algorithmic bias, data privacy, informed consent, and accountability. Patients must be aware of …
Published in International Journal of Biomedical Innovations and Engineering · Vol. 3, Issue 1, 2025 · pp. 23–28 Read article
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Developing a Chatbot System Utilizing Artificial Intelligence and Natural Language Processing
Abstract: Software applications commonly feature a user interface that falls into broad categories, namely graphical user interface (GUI), text-based UI, or a blend of both. This interface is predominantly employed in web-based and desktop applications. A chatbot, designed to engage with users, operates through the storage and retrieval of session data. It proves particularly beneficial in situations where obtaining information about individuals who are not affiliated as students or employees of …
Published in Journal of Software Engineering Tools & Technology Trends · Vol. 11, Issue 1, 2024 · pp. 24–29 Read article
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Machine Learning Driven Mobile Price Prediction Using Feature Selection and Parameter Optimization
Abstract: Machine learning calculations are utilized in many fields like money, training, industry, medication, and online business. Machine learning calculations show execution contrasts relying upon the dataset and handling steps. Picking the right calculation, preprocessing and post-handling techniques have incredible significance in accomplishing great outcomes. The Random Forest classifier, K-nearest neighbor classifier, and support vector machine methods are evaluated to forecast mobile phone price categories. The “prediction” dataset which is taken …
Published in Current Trends in Information Technology · Vol. 14, Issue 3, 2024 · pp. 18–25 Read article
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IoT-based Black Box Monitoring for Vehicle Crash Data Analysis and Improving Safety
Abstract: Road accidents are a significant global concern. This project proposes an Internet of Things (IoT)-based black box monitoring system for vehicles to enhance road safety through comprehensive crash data analysis. The system expands on traditional black boxes by incorporating various sensors (accelerometers, gyroscopes, GPS) and potentially in-cabin cameras (with privacy safeguards). This data offers a deeper understanding of crash dynamics, including impact severity, vehicle motion, and safety system deployment timing. …
Published in Research & Reviews: A Journal of Embedded System & Applications · Vol. 12, Issue 3, 2024 · pp. 7–13 Read article
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IoT-Enabled Remote Patient Monitoring System Using Wearable Sensors
Abstract: In recent years, the Internet of Things (IoT) has revolutionized healthcare by enabling seamless connectivity between patients, medical devices, and healthcare professionals. The increasing demand for continuous health monitoring and early disease detection has driven the development of IoT-based remote patient monitoring systems. This paper presents an IoT-enabled framework that integrates wearable physiological sensors, wireless communication modules, and cloud- based analytics to facilitate real-time health tracking. The proposed system continuously …
Published in Recent Trends in Electronics Communication Systems · Vol. 13, Issue 1, 2026 Read article
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Analysis of Gold Price Trend Using the Hidden Markov Model
Abstract: This study aims to analyze the behavior of gold prices in India through a two-state Hidden Markov Model (HMM). We first formulated crucial parameters, such as the Transition Probability Matrix (TPM), Initial Probability Vector (IPV), and Emission Probability Matrix (EPM). Subsequently, we constructed a hidden Markov probability distribution and evaluated Pearson’s coefficients to gauge the correlations separately for each state. The goodness of fit of the developed model was assessed …
Published in Research & Reviews: Discrete Mathematical Structures · Vol. 11, Issue 2, 2024 · pp. 7–16 Read article
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Unveiling the Engine of Efficiency: Exploring the Vital Dimensions of Warehousing for Optimal Operational Performance
Abstract: This research endeavours to comprehensively explore the multifaceted dimensions of warehousing that significantly influence operational efficiency within the bustling industrial nexus of the National Capital Region (NCR), encompassing a diverse array of warehouse types in the vicinity of Delhi-NCR. Employing a meticulously crafted structured questionnaire, respondents provided insights through a Likert scale, ranging from 1 = Strongly Disagree to 5 = Strongly Agree. The data collection process, utilizing stratified sampling …
Published in Journal of Production Research & Management · Vol. 14, Issue 1, 2024 · pp. 29–38 Read article
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Artificial Neural Network Based Prediction of Impact Loads and Thickness in CFRP and GFRP Composite Laminates
Abstract: Recent technological advancements, particularly the integration of neural networks, have facilitated a predictive approach to complex engineering problems, especially those involving composite materials with directional properties. The scarcity of literature on predicting impact damage using experimental and ultrasonic flaw detection data motivated this study. Experimental assessment of impact damage on carbon fiber/epoxy (CFRP) and glass fiber/epoxy (GFRP) composites was conducted using low-velocity drop weight impact testing. Damage assessment employed an …
Published in International Journal of Fracture Mechanics and Damage Science · Vol. 2, Issue 1, 2024 · pp. 34–45 Read article
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Detection and Classification of Diabetic Retinopathy Using Deep Learning Techniques
Abstract: This project delves into the evaluation of three prominent deep learning architectures Basic CNN, ResNet, and DenseNet for their efficacy in detecting diabetic retinopathy from retinal images. Utilizing a diverse dataset, the study employs standard deep learning frameworks to train and validate each model. The focus extends to exploring the potential benefits of transfer learning on a limited dataset. Evaluation metrics like specificity, sensitivity, and accuracy are employed for a …
Published in Research and Reviews : A Journal of Medical Science and Technology · Vol. 13, Issue 2, 2024 · pp. 64–69 Read article
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A Web Application for Predicting Diabetes Using Machine Learning Methods
Abstract: Diabetes is a long-term disease caused by high glucose quantity in the blood. It has the potential to result in serious health complications like heart disease, hypertension, and ocular damage. It is good to identify any health issues as early as possible to get the right medical treatment and make necessary lifestyle adjustments. One makes use of machine learning techniques to predict diabetes and develop treatment options using actual cases. …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 11, Issue 3, 2024 · pp. 92–102 Read article